most citedDG-TTA: Out-of-domain Medical Image Segmentation through Augmentation and Descriptor-driven Domain Generalization and Test-Time Adaptation

1 citations · 1 across the 1 of their papers we have counts for

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1 paper

cs.CV2023★ 1 cited

DG-TTA: Out-of-domain Medical Image Segmentation through Augmentation and Descriptor-driven Domain Generalization and Test-Time Adaptation

Christian Weihsbach, Christian N. Kruse, Alexander Bigalke +1

Purpose: Applying pre-trained medical deep learning segmentation models on out-of-domain images often yields predictions of insufficient quality. In this study, we propose to use a…